Artificially Intelligent Queueing Modeling Approach to Analyzing and Improving Health Care Systems

Abstract

A wide variety of mathematical and computational techniques and programming are considered under operational research to deal with problems connected with applied science. One such technique is queueing theory, which can solve and analyze the waiting lines mathematically, such as the average number of customers waiting in a queue. Now a days, queueing models are used to analyze and suggest congestion minimization in the service and optimize inappropriate delivery time in various airlines, banking, restaurants, healthcare systems, etc. Therefore, keeping in view the potential and versatility of the queueing model, we intend to apply it in healthcare systems (HCSs) to analyze and improve healthcare systems by evaluating its performance measures. Much less work has been undertaken and reported in this direction by using AI tempered queueing models. Now, it is a need of the hour to couple such methodology with the HCSs to include accuracy and precision in predicting its performance measures. In this light, to bridge this critical gap, the AI queueing model is proposed to apply in the analysis of HCSs in the present proposal. Artificial Intelligence and its techniques can easily handle the analysis of the healthcare systems performance appropriately as required by todays industry 4.0.